AI Medical Compendium Journal:
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA

Showing 1 to 10 of 41 articles

Beyond traditional orthopaedic data analysis: AI, multimodal models and continuous monitoring.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA Mar 22, 2025
Multimodal artificial intelligence (AI) has the potential to revolutionise healthcare by enabling the simultaneous processing and integration of various data types, including medical imaging, electronic health records, genomic information and real-ti...
Artificial Intelligence Data Analysis Electronic Health Records Orthopedic Procedures Orthopedics Humans
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Evaluation of a novel robotic testing method for stability and kinematics of total knee arthroplasty.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA Oct 24, 2024
PURPOSE: This work developed a novel preclinical test of total knee replacements (TKRs) in order to explain TKR instability linked to patient dissatisfaction. It was hypothesized that stability tests on the isolated moving prostheses would provide no...
Biomechanical Phenomena Robotics Knee Joint Humans Knee Prosthesis Prosthesis Design Joint Instability Materials Testing Patient Satisfaction
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Machine learning model outperforms the ACS Risk Calculator in predicting non-home discharge following primary total knee arthroplasty.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA Sep 30, 2024
PURPOSE: Despite the increase in outpatient total knee arthroplasty (TKA) procedures, many patients are still discharged to non-home locations following index surgery. The ability to accurately predict non-home discharge (NHD) following TKAs has the ...
Arthroplasty, Replacement, Knee Middle Aged Risk Assessment Patient Discharge Aged Aged, 80 and over Male Humans Retrospective Studies Female Neural Networks, Computer Machine Learning
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Methodology and development of a machine learning probability calculator: Data heterogeneity limits ability to predict recurrence after arthroscopic Bankart repair.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA Sep 26, 2024
PURPOSE: The aim of this study was to develop and train a machine learning (ML) algorithm to create a clinical decision support tool (i.e., ML-driven probability calculator) to be used in clinical practice to estimate recurrence rates following an ar...
Arthroscopy Recurrence Joint Instability Risk Factors Adult Male Shoulder Dislocation Bankart Lesions Humans Machine Learning Algorithms Retrospective Studies Female
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High accuracy in lower limb alignment analysis using convolutional neural networks, with improvements needed for joint-level metrics.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA Sep 22, 2024
PURPOSE: Evaluation of long-leg standing radiographs (LSR) is a standardised procedure for analysis of primary or secondary deformities of the lower limbs. Deep-learning convolutional neural networks (CNN) offer the potential to enhance radiological ...
Humans Reproducibility of Results Aged Male Neural Networks, Computer Radiography Retrospective Studies Knee Joint Female Arthroplasty, Replacement, Knee Osteoarthritis, Knee Middle Aged Convolutional Neural Networks Lower Extremity
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Machine-learning models for shoulder rehabilitation exercises classification using a wearable system.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA Aug 18, 2024
PURPOSE: The objective of this study is to train and test machine-learning (ML) models to automatically classify shoulder rehabilitation exercises.
Humans Machine Learning Algorithms Middle Aged Exercise Therapy Female Case-Control Studies Rotator Cuff Injuries Adult Wearable Electronic Devices Male
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The artificial intelligence advantage: Supercharging exploratory data analysis.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA Jul 31, 2024
Explorative data analysis (EDA) is a critical step in scientific projects, aiming to uncover valuable insights and patterns within data. Traditionally, EDA involves manual inspection, visualization, and various statistical methods. The advent of arti...
Humans Artificial Intelligence Machine Learning Data Analysis Algorithms
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Application of a machine learning and optimization method to predict patellofemoral instability risk factors in children and adolescents.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA Jul 21, 2024
PURPOSE: Conservative treatment remains the standard approach for first-time patellar dislocations. While risk factors for patellofemoral instability, a common paediatric injury, are well-established in adults, data concerning the progression of paed...
Joint Instability Machine Learning Patellar Dislocation Retrospective Studies Child Humans Female Magnetic Resonance Imaging Risk Factors Patellofemoral Joint Male Adolescent
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Artificial intelligence-based assessment of leg axis parameters shows excellent agreement with human raters: A systematic review and meta-analysis.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA Jul 21, 2024
PURPOSE: The aim of this study was to conduct a systematic review and meta-analysis on the reliability and applicability of artificial intelligence (AI)-based analysis of leg axis parameters. We hypothesized that AI-based leg axis measurements would ...
Femur Leg Humans Knee Joint Tibia Hip Joint Artificial Intelligence Reproducibility of Results Radiography
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Achieving high accuracy in meniscus tear detection using advanced deep learning models with a relatively small data set.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA Jul 17, 2024
PURPOSE: This study aims to evaluate the effectiveness of advanced deep learning models, specifically YOLOv8 and EfficientNetV2, in detecting meniscal tears on magnetic resonance imaging (MRI) using a relatively small data set.
Deep Learning Magnetic Resonance Imaging Tibial Meniscus Injuries Female Adult Male Humans
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